Falls are one of the greatest health risk factors for elderly people. About one third of older people above the age of 65 fall at least once a year.
Many of these falls could be avoided by early identification of fall risk and the application of effective and targeted fall prevention programs. In particular, home-based fall prevention exercise programs that include balance training, muscle strengthening and a walking plan have been shown to be effective in reducing the occurrence of falls.
Thus, fall risk assessments are carried out on users to identify those at high risk of falling, and the exercises selected for the fall prevention program are tailored to the user to maximise their benefit in reducing the fall risk.
In some cases, a fall risk assessment can be made by the user filling in a questionnaire to provide a subjective estimate of their fall risk. For example the user can fill in the “Review your risk” questionnaire at the website www.learnnottofall.com. The answers to the questionnaire can be used to provide feedback in the form of advice and recommended exercises for minimising the fall risk.
In other cases, caregivers or healthcare professionals can provide a much better estimation of fall risk by making an objective assessment of physical performance, which can be based for example on walking (including an assessment of the user's gait), strength, balance including standing still) and reaction time. One particular assessment involves the ‘sit-to-stand’ (STS) transfer which can be used as a strength and balance performance measure and thus a measure of fall risk. In this assessment, the power exerted by the user in standing up from a sitting position is measured. Other assessments include a timed-up-and-go (TUG) test in which the user stands up from a chair, walks a certain distance and returns to the chair. The time the user consumes in doing so is a measure of their fall risk. More elaborate assessments include the Physiological Profile Assessment (PPA) in which a set of multiple characteristics are evaluated.
However, for objectively determining fall risk, people are required to regularly present themselves at a clinic, where typically expensive dedicated hardware and clinicians are located. This way of assessing fall risk is costly. The need to make and keep to appointments results in a low monitoring/observation rate by the users. In many cases, people only present themselves for the first time at the clinic after a fall has occurred, and it may be that the earlier application of a fall prevention program could have prevented that fall from occurring.
Thus, it is desirable to be able to obtain an objective measurement of a user's fall risk while they are in their home environment without assistance from or visiting a care provider or healthcare professional. However, individuals do not want to buy bulky and expensive dedicated hardware like a camera system, a treadmill or a force plate that needs to be installed in the home. Moreover, the need for individuals to have to set up complex test environments should be avoided.
It is known in the art to provide devices that collect long-term movement data of normal daily behaviour and that calculate a fall risk from the long-term movement data. For example US 2012/0119904 describes the use of a pedometer that monitors the steps taken by the patient during the day. However, this information is gathered in free living conditions and its usefulness in determining fall risk is limited as it largely depends on the environmental challenges (e.g. stairs) and the movement intention of the individual. Also information on the physical capabilities that enable the individual to adequately respond to unforeseen events (such as a stumble) to prevent a fall cannot be accurately captured. Another problem is that a large amount of data needs to be collected, which means that a large battery is required since the device has to be collecting and storing and/or processing the data for a long period of time.
Thus, there is a need for a system and method that enables a user (and/or a remotely-located clinician) to quickly and easily estimate the user's fall risk in a home or other non-clinical environment while ensuring that the user-worn or carried device remains generally unobtrusive and does not result in the user having to carry or wear additional hardware.